Neural-network-supported basis optimizer for the configuration interaction problem in quantum many-body clusters: Feasibility study and numerical proof

Bilous P, Thirion L, Menke H, Haverkort MW, Pálffy A, Hansmann P (2025)

Publication Type: Journal article

Publication year: 2025

Journal

Physical Review B American Physical Society

Book Volume: 111

Article Number: 035124

Journal Issue: 3

DOI: 10.1103/PhysRevB.111.035124

Abstract

A neural-network approach to optimize the selection of Slater determinants in configuration interaction calculations for condensed-matter quantum many-body systems is developed. We exemplify our algorithm on the discrete version of the single-impurity Anderson model with up to 299 bath sites. Employing a neural network classifier and active learning, our algorithm enhances computational efficiency by iteratively identifying the most relevant Slater determinants for the ground state wave function. We benchmark our results against established methods and investigate the efficiency of our approach compared to another basis truncation scheme without a neural network. Our algorithm demonstrates a substantial improvement in the efficiency of determinant selection, yielding a more compact and computationally manageable basis without compromising accuracy. Given the straightforward application of our neural-network-supported selection scheme to other model Hamiltonians of quantum many-body clusters, our algorithm can significantly advance selective configuration interaction calculations in the context of correlated condensed matter.

Authors with CRIS profile

Louis Thirion Professur für Theoretische Physik mit dem Schwerpunkt Molekulare Materialien Henri Menke Professur für Theoretische Physik mit dem Schwerpunkt Molekulare Materialien Philipp Hansmann Professur für Theoretische Physik mit dem Schwerpunkt Molekulare Materialien

Involved external institutions

Max-Planck-Institut für die Physik des Lichts (MPL) / Max Planck Institute for the Science of Light DE Germany (DE) Ruprecht-Karls-Universität Heidelberg DE Germany (DE) Julius-Maximilians-Universität Würzburg DE Germany (DE)

How to cite

APA:

Bilous, P., Thirion, L., Menke, H., Haverkort, M.W., Pálffy, A., & Hansmann, P. (2025). Neural-network-supported basis optimizer for the configuration interaction problem in quantum many-body clusters: Feasibility study and numerical proof. Physical Review B, 111(3). https://doi.org/10.1103/PhysRevB.111.035124

MLA:

Bilous, Pavlo, et al. "Neural-network-supported basis optimizer for the configuration interaction problem in quantum many-body clusters: Feasibility study and numerical proof." Physical Review B 111.3 (2025).

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